The development of mathematical procedures for the reconstruction of images of the internal structure of a body has been under consideration since the beginning of this century. In general, tomography systems include a radiation source arranged to direct x-ray or other radiation through a portion of a body and one or more sensors disposed to receive radiation passing through the body which provide a signal representative of received radiation intensity. The source and associated sensors are movable relative to the body to provide a plurality of projections during a predetermined scan to produce data from the several projections. Various techniques of image reconstruction have been proposed by which data from the projections is assembled into a final image. Such techniques have employed iterative algebraic reconstruction, Fourier transformations, and convolution filtering.
During recent years, great interest has been shown in computerized tomography by which a digital computer is employed for image reconstruction. Present tomography systems generally employ costly, general purpose computers for the reconstruction processing, and these systems have not been wholly satisfactory for a number of reasons, including expense, limited resolution and the requirements of long periods of time following completion of a scan before a reconstructed image is produced. In order to accomplish the large number of complex calculations required for producing a final image, a sophisticated high-speed computer is required, but even with such a computer, considerable time is required for production of the final image.
Some tomography processing systems have employed separate, dedicated processors controlled by a central computer to perform one or more of the correction, convolution and image reconstruction functions. However, in these systems, the dedicated processors are independent of one another, and data is transferred between the dedicated processors via the central computer, which controls each of the processors and to which each of the dedicated processors is connected. This configuration reduces somewhat the complexity required of the computer; but the speed of the system is restricted by the input/output speed of the computer, and for a high-speed system, an expensive high-speed computer is still required.
In order to reduce the time required to produce a final image or to reduce the sophistication required of the computer, approximations have been made in the algorithms implemented by the above-described system to reduce computing time. However, these approximations have resulted in less than optimum imaging results.